Methods and Systems for Virtual Problem Based Learning

ABSTRACT

A computer-implemented method includes selecting, by a virtual problem-based learning (PBL) system, information indicative of a medical profile of a patient; accessing, by the virtual PBL system, information indicative of a team of students using the virtual PBL system; generating, by the virtual PBL system and based on the medical profile, an medical PBL schema comprising a medical problem to be solved by the team of students; generating a plurality of sections in the medical PBL schema, with each section promoting solving of the medical problem, and with each section associated with (i) a private work environment for a student to privately analyze the medical problem, and (ii) a shared, anonymous work environment for the students to view analysis performed by other students in solving the medical problem; and transmitting, to one or more client systems used by the students participating in the virtual problem-based learning system, the medical PBL schema.

CLAIM OF PRIORITY

This application is a continuation of and claims priority under 35U.S.C. §120 to U.S. application Ser. No. 13/874,947, which was filed May1, 2013, which claims priority under 35 U.S.C. §119(e) to provisionalU.S. Patent Application 61/783,924, filed on Mar. 14, 2013, the entirecontents of each of which are hereby incorporated by reference.

BACKGROUND

In an example, students may solve a problem through collaboration.

SUMMARY

In general, one innovative aspect of the subject matter described inthis specification can be embodied in methods that include the actionsof selecting, by a virtual problem-based learning (PBL) system,information indicative of a medical profile of a patient; accessing, bythe virtual PBL system, information indicative of a team of studentsusing the virtual PBL system; generating, by the virtual PBL system andbased on the medical profile, an medical PBL schema comprising a medicalproblem to be solved by the team of students; generating a plurality ofsections in the medical PBL schema, with each section promoting solvingof the medical problem, and with each section associated with (i) aprivate work environment for a student to privately analyze the medicalproblem, and (ii) a shared, anonymous work environment for the studentsto view analysis performed by other students in solving the medicalproblem; and transmitting, to one or more client systems used by thestudents participating in the virtual problem-based learning system, themedical PBL schema.

Other embodiments of this aspect include corresponding computer systems,apparatus, and computer programs recorded on one or more computerstorage devices, each configured to perform the actions of the methods.A system of one or more computers can be configured to performparticular operations or actions by virtue of having software, firmware,hardware, or a combination of them installed on the system that inoperation causes or cause the system to perform the actions. One or morecomputer programs can be configured to perform particular operations oractions by virtue of including instructions that, when executed by dataprocessing apparatus, cause the apparatus to perform the actions.

The foregoing and other embodiments can each optionally include one ormore of the following features, alone or in combination. In particular,one embodiment may include all the following features in combination. Insome implementations, the features include receiving, from the one ormore client systems, analysis information indicative of an analysisperformed by the one or more students; evaluating the received analysisinformation; generating, based on evaluating, feedback information; andtransmitting the feedback information to at least one of the one or moreclient systems. In still other implementations, the features includeassociating one or more research tools with the private workenvironment, wherein the one or more research tools are selected from agroup consisting of an Internet browser and an instant messaging tool.

In yet other implementations, the features include transmitting, to atleast one of the one or more client devices, outcome data indicative ofoutcomes of patients with medical profiles that are similar to theselected medical profile, with the outcome data comprising comorbiditydata. In still other implementations, the features include receiving,from the one or more client systems, analysis information indicative ofan analysis performed by the one or more students; for a particularstudent, populating the private work environment of the student with aportion of the analysis information that is associated with theparticular student; generating an anonymized view of the private workenvironment of the student; populating the shared, anonymous workenvironment with the anonymized view of the private work environment ofthe particular student and with anonymized views of other private workenvironments of others of the students.

In still other implementations, the features include receiving, from atleast one of the one or more client systems used by a first student,information indicative of an annotation of information displayed in oneof the anonymized views of a second student, with the first studentdiffering from the second student; and updating the one of theanonymized views with the received annotation to promote learning by thesecond student. In yet other implementations, the feature include for aparticular first section: receiving, from the one or more clientsystems, first analysis information indicative of an analysis performedby the one or more students; determining, from the received firstanalysis information, first recommended actions that are recommended byeach of the students; determining an inconsistency among the firstrecommended actions; providing, to the one or more client systems,evaluation information to promote an understanding by the students ofthe medical problem; receiving, from the one or more client systems,second analysis information indicative of another analysis performed bythe one or more students; determining, from the received second analysisinformation, second recommended actions that are recommended by each ofthe students; determining consistency among the second recommendedactions; causing, based on determination of the consistency, the medicalPBL schema to progress from the first section to the second section.

In still other implementations, the features include retrievinginformation indicative of a correct action for the particular firstsection; responsive to determining the consistency among the secondrecommended actions, generating a notification of whether the secondrecommended actions corresponds to the correct action. In yet otherimplementations, the second recommended actions comprise an action toperform surgery. In still other implementations, the feature includegenerating highlighting tools for annotation of the medical profile,wherein each one of the highlighting tools corresponds to attributes ofthe medical problem; receiving, by the computer system, informationindicative of annotations of the medical profile; determining, by thecomputer system, at least a portion of the annotations that is selectedusing a particular one of the highlighting tools; identifying which oneof the attributes corresponds to the particular one of the highlightingtools; and storing, in a data repository, the determined portion of theannotations in association with the identified one of the attributes.

All or part of the foregoing may be implemented as a computer programproduct including instructions that are stored on one or morenon-transitory machine-readable storage media, and that are executableon one or more processing devices. All or part of the foregoing may beimplemented as an apparatus, method, or electronic system that mayinclude one or more processing devices and memory to store executableinstructions to implement the stated functions.

The details of one or more embodiments of the subject matter of thisspecification are set forth in the accompanying drawings and thedescription below. Other features, aspects, and advantages of thesubject matter will become apparent from the description, the drawings,and the claims.

DESCRIPTION OF DRAWINGS

FIG. 1A is a block diagram of a PBL system.

FIG. 2 is a block diagram of components of the PBL system.

FIGS. 1B, 3A, 3B, 3C 4-6 are screen images of graphical user interfacesgenerated by the PBL system.

FIGS. 7-9 are flow charts of processes executed by the PBL system.

DETAILED DESCRIPTION

Referring to FIG. 1A, network environment 100 includes client devices102, 108, network 110, server 112 and data repository 114. Client device102 is used by user 104. Client device 108 is used by user 105. In thisexample, users 104, 105 may be medical students who are studying formedical exams. Server 112 is a system for virtual, online promotingproblem based learning (PBL) for medical students, including, e.g.,users 104, 105. PBL is a student-centered pedagogy in which studentslearn about a subject through the experience of problem solving. PBLincludes problems (e.g., medical problems) that are designed tochallenge student to use problem solving techniques, to useself-directed learning strategies, to use team participation skills insolving the problem, and in using disciplinary knowledge in solving aproblem. In PBL, a student analyzes a problem and determines what mustbe learned to solve the problem. The student constructs his/her ownknowledge by looking for meaning and order. The student interprets whathe/she hears, reads and sees based on past experiences and knowledge. Inthis example, knowledge has personal meaning and is constructed andorganized by the learner. Learning is successful when the studentdemonstrates problem solving and the appropriate application of his/herknowledge.

To promote PBL, server 112 generates medical PBL schema 120, whichincludes a series of sections that promote solving of a medical problem.In an example, server 112 includes a virtual PBL system. Medical PBLschema 120 is based on a medical problem. A section in a medical PBLschema includes various information, including, e.g., a patient profile,videos, symptom information, and so forth. Medical PBL schema 120includes sections 122, 124, 126.

In an example, a section in medical PBL schema 120 includes a privatework environment, which is an online space (e.g., a virtual space) inwhich a student can make notes about the material presented in asection, edit the notes and review and study the material presented in asection. A section also includes an anonymous work environment, whichincludes an online space in which students can view the work done byother students (e.g., notes of other students) in the private workenvironment of the other students. In the anonymized work environment,the work of other students is presented in an anonymized format suchthat names of the students and other identifying information is removed.

In the example of FIG. 1A, section 122 includes private workenvironments 128, 130 and anonymous work environment 132 (e.g., a publicwork environment that may be shared by multiple users). In this example,a private work environment is assigned to a particular user andrepresents a virtual work space in which the particular user can studyand prepare notes. In this example, user 104 uses private workenvironment 128 and user 105 uses private work environment 130. Section122 also includes anonymous work environment 132 for display ofanonymized notes and other work product of users 104, 105.

Medical PBL schema 120 includes sections 124, 126. Section 124 includesprivate work environments 134, 136, which are used by users 104, 105,respectively. Section 124 also includes anonymous work environment 138,e.g., for presentation of anonymized notes of users 104, 105 for section124. Section 126 includes private work environments 140, 142, which areused by users 104, 105, respectively. Section 124 also includesanonymous work environment 144, e.g., for presentation of anonymizednotes of users 104, 105 for section 126.

Each of sections 122, 124, 126 includes solving information 127, 129,131, respectively. As previously described, medical PBL schema 120 isbased on a medical problem. For example, the problem may be correctlydiagnosing a disease of a patient. In another example, the problem maybe determining a type of surgery to be performed to address a medicalcondition of the patient. In still another example, the type of problemmay be correctly identifying a type of implant to be inserted for apatient. In an example, an administrator (e.g., a medical doctor orother medical service provider) inputs into server 112 informationspecifying the problem to be solved (e.g., the problem is to correctlydiagnose a medical condition of the patient). The administrator alsoinputs into server 112 answer information 152. Generally, answerinformation includes information specifying an answer to the medicalproblem. For example, the answer information may specify that thecorrect answer is that the patient suffers from dyslexia or anothermedical condition.

To assist the students (e.g., users 104, 105) in correctly identifyingthe answer to the medical problem represented in medical PBL schema 120,server 112 generates solving information. Generally, solving informationincludes information that promotes the solving of a medical problem. Forexample, the solving information includes information that promotesidentification of the answer to a medical problem. Server 112 may beconfigured to automatically generate problem solving information (alsoreferred to herein as solving information), as described in furtherdetail below.

In an example, server 112 obtains, from data repository 114, medicalproblem information 150, including, e.g., information indicative of amedical problem to be solved by the students through interaction withthe medical PBL schema 120. In this example, the medical problem isproper identification of a type of implant to be used during a surgicaloperation. The answer to the problem is that a particular type of hipimplant should be used in performed a hip replacement surgery. Topromote learning in a way that assists the students in answering thequestion, server 112 identifies various sub-problems to be addressed insolving the medical problem represented in the medical PBL schema 120.These various sub-problems include sub-problem I which is identificationof a medical condition of a patient (e.g., degenerative hip disease) andsub-problem II which is identification of a type of surgery to beperformed on the patient (e.g., hip replacement surgery). Answers tosub-problems I and II are used in identifying the main problem of themedical PBL schema 120, e.g., identification of a particular implant tobe used during the hip replacement.

In this example, section 122 is associated with sub-problem I andpromotes solving of sub-problem I. Section 124 is associated withsub-problem II and promotes solving of sub-problem II. Section 126 isassociated with the main problem of medical PBL schema and promotessolving of the main problem. In an example, an operator of environment100 and/or associates the sub-problems with each of sections 122, 124,respectively. In another example, server 112 accesses in data repository114 information indicative of various sub-problems to be solved topromote learning and proper identification of the main problem (e.g.,the primary problem associated with section 126).

To promote solving of the sub-problem associated with section 122,server 112 generates solving information 127. In an example, an operatormay be configured to upload solving information 127 into server 112 andto specify that solving information 127 is to be associated with section122 of medical PBL schema 120. In another example, server 112 generatessolving information 127 by accessing a medical profile 154 of a patientof a specified type, e.g., a medical profile of a patient possessing themedical condition. Server 112 parses the medical profile 154 and selectsinformation for inclusion in solving information 127. For example,medical problem information 150 may include information indicative aname of a disease (e.g., degenerative hip disease) that is experiencedby a patient. Server 112 may be configured to identify, in medicalproblem information 150, the name of the disease and to select from themedical profile 154 information that is indicative of the disease (e.g.,symptoms of the disease). In another example, server 112 accesses indata repository 114 a mapping of disease names to symptoms of thedisease. Based on the mapping, server 112 identifies symptoms of thedisease. Server 112 populates solving information 127 with theidentified symptoms and/or with portions of medical profile 154 thatpertain to the disease. In this example, solving information includesvarious types of information to promote students in solving subproblemsand/or a primary problem of the PBL problem. For example, solvinginformation may include symptoms. Solving information may also includeoutcome data indicative of outcomes of other patients with medicalprofiles that are similar to the medical profile on which medical PBLschema is based, with the outcome data comprising comorbidity data. Theoutcomes of the other patients (e.g., including the comorbidity data)may assist a student in predicting an outcome for the patient that isrepresented in medical PBL schema 120. The outcomes of the otherpatients (e.g., including the comorbidity data) may assist a student indetermining a hypothesis, problem list and/or recommended action for thepatient that is represented in medical PBL schema 120.

In the example of FIG. 1A, users 104, 105 are presented with solvinginformation 127. Based on viewing solving information 127, users 104,105 transmit, to server 112, analysis information 146, 148,respectively. Generally, analysis information includes informationindicative of a user's analysis of the presented solving information.The analysis information may include notes of the user and a recommendedaction (e.g., an answer to a primary problem and/or an answer to asub-problem). Client devices 102, 108 send analysis information 146, 148to server 112, respectively. In an example, users may use private workenvironments 128, 130 for entry of analysis information 146, 148,respectively. For example, client device 102 may render a visualrepresentation of private work environment 128. Through private workenvironment 128, user 104 may enter analysis information 146. In anotherexample, client device 102 may transmit analysis information 146 toserver 112. In response, server 112 may populate private workenvironment 128 with analysis information 146.

In this example, analysis information 146 includes a recommended actionthat was determined by user 104, including, e.g., a recommended actionof a type of condition that is being experienced by the patientrepresented in solving information 127. Using analysis information 146,148, server 112 generates information for population of anonymous workenvironment 132. In anonymous work environment, users 104, 105 can viewthe work of each other and can edit the work of each other, as describedin further detail below.

In the example of FIG. 1A, users 104, 105 may access various tools inanalyzing solving information 127. For example, users 104, 105 mayaccess the Internet to look up types of medical conditions associatedwith the symptoms presented in solving information. In this example,user 104, 105 may access the Internet via the private work environments.In another example, section 122 includes various videos to assists auser in correctly identifying a condition of the patient presented insolving information 127.

Each item of analysis information 146, 148 includes a recommendedaction. Server 112 is configured to compare the recommended actionsincluded in each of analysis information 146, 148. Upon determination ofa match between the recommended action (e.g., consistency among therecommended actions), server 112 enables users 104, 105 to progress tothe next section of medical PBL schema 120, e.g., section 124. In theexample of FIG. 1, analysis information 146, 148 is for section 122 andis based on review of solving information 127, e.g., by users 104, 105.

Analysis information 146, 148 may include identifying information ofusers 104, 105, respectively, including, e.g., a user name of theseusers, a unique identifier for these users and so forth. In thisexample, server 112 is configured to remove the identifying information,e.g., to promote an anonymous display of analysis information 146, 148.In this example, anonymous work environment 132 displays the anonymizedanalysis information, e.g., for collaborative review by users 104, 105,as described in further detail below.

In the example of FIG. 1A, following progression by users 104, 105 tosection 126, solving information 131 is transmitted to client devices102, 108 for display to users 104, 105, respectively. In this example,section 126 is a section that is representative of the main problem,e.g., identification of a particular implant to be used during the hipreplacement. As previously described, the answer to this main problem isincluded in answer information 152. Following review and analysis ofsolving information 131, client devices 102, 108 send additionalanalysis information (not shown) to server 112. This additional analysisinformation includes recommended actions, e.g., answers to the mainproblem. In this example, server 112 compares the recommended actionsincluded in the additional analysis information. If server 112determines a match between the recommended actions, then the server 112determines that the users 104, 105 agreed on a consensus for arecommended action to take, e.g., an answer to the main medical problemrepresented in medical PNL schema 120. In this example, server 112compares the consensus recommended action to answer information 152. Ifthe consensus recommended action matches answer information 152, server112 notifies users 104, 105 that they correctly solved the medicalproblem. If the consensus recommended action does not match answerinformation 152, server 112 notifies users 104, 105 that theyincorrectly solved the medical problem and provides users 104, 105 withanswer information 152 so that users 104, 105 may view the correctanswer.

In another example, server 112 determines a mismatch between therecommended actions included in the analysis information for section126, then the server 112 determines that the users 104, 105 failed toagree on a consensus for a recommended action to take, e.g., an answerto the main medical problem represented in medical PNL schema 120. Inthis example, server 112 does not compare the received recommendedactions to answer information 152. Rather, server 112 notifies users104, 105 that have not reached a consensus recommended action andprovides users 104, 105 with (i) additional time to review solvinginformation 131 and to generate new recommended actions, (ii)additionally solving information with which to generate new recommendedactions, and/or (iii) evaluation information. Evaluation information isadditional information that provides a student with additional hints,medical data, learning materials and so forth to promote correctdetermination of a recommended action.

Referring to FIG. 1B, server 112 generates graphical user interface 170,e.g., to welcome a patient upon accessing the PBL system. In thisexample, the PBL system may be configured to host various types ofstudies, including, e.g., a personalized study and a group study, inwhich users collaborate with other users in a PBL environment. Control172 enables a user to view a personalized study and/or to generate astudy. Control 173 enables a user to view a group study to which theuser has been selected for participation.

Graphical user interface 170 includes portion 174 to provide a user withan overview of a group study and to provide the user with a “currentstatus” of the group study, e.g., a next discussion that the user needsto participate in and/or a listing of current notes and othercontributions that have been made to the group by other users of thegroup. Graphical user interface 170 also includes controls 176,selection of which enables a user to view tools that are available forengaging in the group study. These tools may include various types ofasset information, as described in further detail below. Graphical userinterface 170 also includes control 178, selection of which enables auser to view information indicative of other users who are participatingin the group study. Graphical user interface 170 also includes control180, selection of which enables a user to view data associated with thegroup study. This data may include progress reports of the group,including, e.g., the progress report shown in portion 536 of FIG. 5A.

FIG. 2 is a block diagram of components of network environment 100. InFIG. 2, client devices 102, 108 can be any sort of computing devicescapable of taking input from a user and communicating over network 110with server 112 and/or with other client devices. For example, clientdevices 102, 108 can be mobile devices, desktop computers, laptops, cellphones, personal digital assistants (“PDAs”), servers, embeddedcomputing systems, and so forth.

Server 112 can be any of a variety of computing devices capable ofreceiving data, such as a server, a distributed computing system, adesktop computer, a laptop, a cell phone, a rack-mounted server, and soforth. Server 112 may be a single server or a group of servers that areat a same location or at different locations.

The illustrated server 112 can receive data from client devices 102, 108via input/output (“I/O”) interface 140. I/O interface 140 can be anytype of interface capable of receiving data over a network, such as anEthernet interface, a wireless networking interface, a fiber-opticnetworking interface, a modem, and so forth. Server 112 also includes aprocessing device 148 and memory 144. A bus system 146, including, forexample, a data bus and a motherboard, can be used to establish and tocontrol data communication between the components of server 112.

The illustrated processing device 148 may include one or moremicroprocessors. Generally, processing device 148 may include anyappropriate processor and/or logic that is capable of receiving andstoring data, and of communicating over a network (not shown). Memory144 can include a hard drive and a random access memory storage device,such as a dynamic random access memory, or other types of non-transitorymachine-readable storage devices. Memory 144 stores computer programs(not shown) that are executable by processing device 148 to perform thetechniques described herein.

Referring now to FIG. 3A, server 112 generates graphical user interface300 for display of notes 302. In this example, user 104 reviews solvinginformation 127 (FIG. 1A) and generates notes 302 based on review ofsolving information 127. In an example, portion 302 displays solvinginformation 127 and user 104 makes notes by marking up portions ofsolving information 127 as displayed in graphical user interface 300.Graphical user interface 300 includes controls 304, 306, 308, 310, e.g.,for editing of solving information 127. In this example, each ofcontrols 304, 306, 308, 310 is a highlighting tool that can be used tohighlight portions of text displayed in 302. Each of controls 304, 306,308, 310 is configured to highlight portions of text in portion 302 indifferent colors.

Controls 304, 306, 308, 310 may be used to mark various attributes ofthe solving information, e.g., an attribute indicative of a hypothesis,an attribute indicative of learning objectives, an attribute indicativeof a problem list, an attribute indicative of other information, and soforth. In an example, control 304 is used to highlight portions of textas being indicative of a hypothesis, e.g., a hypothesis about a medicalproblem. Control 306 is used to highlight portions of text as beingindicative of a learning objective, e.g., a learning objective of one ofthe subproblems or the main problem. Control 308 is used to highlighttext to indicate a problem list, e.g., information indicative ofportions of the solving information that a user does not understandand/or wants to further investigate. Control 310 is used to highlightother information, e.g., information that the user thinks may be usefulin solving the problem. In this example, user 104 annotates (e.g.,highlights) solving information 127 that is displayed in portion 302 ofgraphical user interface 300 using one or more of controls 304, 306,308, 310.

Referring to FIG. 3B, server 112 generates graphical user interface 312for display of problem solving information 127 that is annotated (e.g.,using one or more of controls 304, 306, 308, 310) by user 105. Graphicaluser interface 312 includes portion 314 for display of solvinginformation 127 that is annotated by user 105 using controls 305, 306,308, 310.

Referring to FIGS. 3A and 3B, graphical user interface 300 includesannotations 316, 318, 320. Graphical user interface 312 includesannotations 322, 324, each of which may differ from annotations 316,318, 320. In an example, graphical user interface 300 is displayed on adisplay of client device 102. In this example, through a web browser,user 104 selects one or more of controls 304, 306, 308, 310. As use 104selects portions of the solving information 127 displayed in graphicaluser interface 300, client device 102 transmits, to server 112,information indicative of the selected information (e.g., theannotations). In response, server 112 stores in data repository 114, theinformation indicative of the selected information.

Referring to FIG. 3C, server 112 generates graphical user interface 350which may be displayed in a private work environment and may be used forthe annotation of solving information, including, e.g., solvinginformation 127. In this example, graphical user interface 350 includesportion 360 for display of information pertaining to the patient forwhich the users are engaging in PBL to diagnose. This displayedinformation includes referring doctor details, patient details andgenerate notes.

Graphical user interface 350 includes portion 362 for display of solvinginformation. Graphical user interface 350 also includes annotationcontrols 352, 354, 356, 358 for marking portions of solving informationdisplayed in portion 362 as pertaining to a hypothesis, an objective, aproblem and notes, respectively. Graphical user interface 350 alsoincludes note control 364, e.g., for a user to enter informationindicative of a note to be associated with the solving information. Inthe example of FIG. 3C, a user generates note 366, via note control 364.In this example, note 366 is associated with the solving informationdisplayed in portion 362.

Portion 362 also include anatomy control 370, including, e.g., avisualization of one or more portions of the patient's anatomy. Usinganatomy control 370, a user make mark portions of the visualization ofthe patient's anatomy as experiencing one or more symptoms. In thisexample, the user uses anatomy control 370 to include in the user'snotes information specifying that the patient is experiencing a numbnesssensation, a stabbing sensation and a burning sensation. Using anatomycontrol 370, the user may also specify the portions of the patient'sanatomy in which the patient is experiencing these symptoms. Themarkings and information generated through anatomy control 370 arepublished to an anonymous work environment, e.g., when the userspecifies that he/she wishes to anonymously publish his/her notes andwork.

In the example of FIG. 3C, graphical user interface 350 is updated withpublish control 368, e.g., upon the user saving changes to annotationsand/or notes included in the private work environment. Through publishcontrol 368, a user may select to publish an annotated version ofsolving information (e.g., includes notes and information generatedthrough anatomy control 370) to an anonymous work environment, e.g., topromote PBL.

Referring to FIG. 4, server 112 generates graphical user interface 400for display of the annotations of the solving information made by thevarious users. Graphical user interface 400 includes portion 402 fordisplay of annotations made by user 104. Graphical user interface 400includes portion 404 for display of annotations made by user 104.Graphical user interface 400 also includes portion 406 for display ofannotations made by another user of environment 100. The informationdisplayed in each of portions 402, 404, 406 is arranged by annotationtype. There are various annotation types, including, e.g., a hypothesisannotation type, a learning objective annotation type, a problem listannotation type, and other information annotation type. In this example,information that is of the hypothesis annotation type is informationthat is selected using control 304. Information that is of the learningobjectives annotation type is information that is selected using control306. Information that is of the problem list annotation type isinformation that is selected using control 308. Information that is ofthe other information annotation type is information that is selectedusing control 310.

In the example of FIG. 4, portions 408, 416, 424 display information ofthe hypothesis annotation type. Portions 410, 418, 426 displayinformation of the learning objectives annotation type. Portions 412,420, 428 display information of the problem list annotation type.Portions 414, 422, 430 display information of the other informationannotation type. The information displayed in graphical user interface400 is anonymized by server 112, e.g., to enable users 104, 105 andother users to view each other notes and annotations of solvinginformation in a private space.

In an example, user 104 uses control 304 to select a portion of solvinginformation 127 that is displayed in graphical user interface 300. Theselected information is of the hypothesis annotation type, as user 104uses control 304 to select the information. Upon selection of theinformation, client device 102 sends to server 112 (i) informationindicative of the selected information, (ii) information indicative ofthe control that is used to select the information, (iii) informationthat uniquely identifies user 104 (e.g., a user name). Upon receipt ofthe information, server 112 stores in data repository the selectedinformation in association with the information indicative of thecontrol that is used to select the information and in association withthe information that uniquely identifies user 104. When generatinggraphical user interface 400, server 112 generates portions 402, 404,406 for the various users.

In an example, server 112 populates portion 408, e.g., by determining anannotation type associated with portion 408. In this example, server 112uses code for generating graphical user interface 400 in determiningthat portion 408 is for hypothesis annotation information for user 104.In this example, server 112 selects, from data repository 114, a portionof analysis information 146 that was generated using control 304. Theportion of analysis information 146 that was generated using control 304includes portion of solving information 127 that were highlighted usingcontrol 304. In this example, analysis information 146 includesinformation indicative of the highlighted portion of solving information127. Server 112 also removes identifying information from the portion ofanalysis information 147 that is to be displayed in portion 408. Theidentifying information may include, e.g., information specifying a nameof user 104, information specifying an affiliated hospital of user 104and so forth. Server 112 executes similar techniques in populating theother portions (e.g., 410, 412, 414, 416, 418, and so forth) ofgraphical user interface 400.

In an example, server 112 transmits information indicative of graphicaluser interface 400 to client devices 102, 108. In this example, clientdevice 102 renders graphical user interface 400. Through graphical userinterface 400, user 104 may edit (e.g., annotate) other user's work,e.g., to promote the users reaching a consensus action, e.g., as shownin visual representations 432, 434, 436. Graphical user interface 400includes a control (not shown) through which user 104 may generate edits438, 440, 442 (e.g., annotations), e.g., strikethroughs of other user'snotes. In still another example, user 104 may enter text into one ormore portions of graphical user interface 400, e.g., to indicateadditional issues that other users should consider.

In the example of FIG. 4, some of the actions specified in visualrepresentations 432, 434, 436 differ from each other. Based on thismismatch among some of the actions specified in visual representations432, 434, 436, server 112 determines that the users have not reached aconsensus action. That is, server 112 determines an inconsistency amongthe recommended action. Because the users have not yet reached aconsensus action, server 112 may allow the users additional time toreview the solving information. Through the edits (e.g., edits 438, 440,442) that users make to each other's annotations, the users learn fromeach other and may modify a hypothesis, a learning objective, and/or aproblem list, which in turn may lead to users changing their recommendedactions.

Referring to FIG. 5A, server 112 generates graphical user interface 500to promote PBL among users of network environment 100. In the example ofFIG. 5A, graphical user interface 500 includes visualizations 502, 504,506, 508, 510, 512, 514, 516 of users of the PBL system (e.g., server112). A visualization of a user is associated with various informationto promote communication among the various users. For example,visualization 516 is associated with selectable portion 518, selectionof which causes the analysis information that is generated by the userassociated with visualization 516 to be displayed. In an example, thisanalysis information is displayed in a portion of graphical userinterface 400 (FIG. 4). Graphical user interface 500 also includescommunication tools 520, 522, 524, 526. Selection of communicationcontrol 520 allows a user to send the user represented by visualization516 an instant message. In an example, the users of the PBL system areevaluated, e.g., by tutors. In this example, the tutors may evaluate theannotation information and/or the analysis information generated by auser, e.g., to promote the user's identification of a correct action.Graphical user interface 500 also includes communication controls 524,526, e.g., controls for sending a user an email and a note,respectively.

Graphical user interface 500 includes communication controls 528, 530,532, e.g., to promote communication among multiple users of the PBLsystem. Upon selection of control 528, graphical user interface 500displays portion 528, e.g., a visual representation of a note pad. Auser (e.g., a tutor or another user of the PBL system) may enterinformation into portion 528, e.g., to send a note to the other users.Upon selection of control 530, server 112 causes graphical userinterface 500 to be updated with a guide, e.g., information thatpromotes learning that enables the users to reach a consensus action.Upon selection of control 528, graphical user interface 500 is updatedto display note portion 534 in which a user may enter information to beshared with the other users.

Graphical user interface 500 also includes chart 536 for display of theusers' progress through the various section of the PBL. Chart 536includes bars 538, 540, 542, 544. Bar 538 provides a visualization ofthe user's progress of the hypothesis portion of the various sections.Portions of bar 538 are color coded with various colors, e.g., red,yellow and green. A portion of bar 538 is color coded green, e.g., whenall the users have correctly identified a hypothesis for a particularsection specified by the green color. A portion of bar 538 is colorcoded yellow, e.g., when a portion of the users have incorrectlyidentified a hypothesis for a particular section specified by the yellowcolor. A portion of bar 538 is color coded red, e.g., when a thresholdnumber (or amount) of the users have incorrectly identified a hypothesisfor a particular section specified by the yellow color.

Referring to FIG. 5B, server 112 generates graphical user interface 550to promote PBL among users of network environment 100. In the example ofFIG. 5B, graphical user interface 500 includes portion 552 for displayof information indicative of users of the PBL system (e.g., server 112).In this example, a viewer of graphical user interface 550 may viewvisual representations of one of the members of the group. In theexample of FIG. 5B, a user selects visualization 556, e.g., and selectscontrol 558. Upon selection of control 558, the user is presented withcommunication control 554, e.g., for sending of an e-mail to the userrepresented in visualization 556. Graphical user interface 550 alsoincludes asset portion 560, e.g., for display of various types of assetinformation, including, e.g., asset information pertaining to documents,images, video and a virtual examination. In this example, asset portion562 includes various documents, which may include solving information(e.g., solving information 127).

Referring to FIG. 6, server 112 generates graphical user interface 600.In an example, graphical user interface 600 includes graphical userinterface 500 that is updated with portion 602. Portion 602 includes adashboard of information that is available to help students in solving aPBL problem. In an example, the types of information displayed inportion 602 is dependent on a particular section that a group ofstudents are working on. In still another example, the particular itemsof data that are available in portion 602 are based on a particularsection (e.g., section 1.1, section 1.2, etc.) that students are workingon completing.

Portion 602 includes asset information 604, video information 606, imageinformation 608, and virtual examination information 610. Assetinformation 604 includes information indicative of various documents toassist students in solving a PBL problem. These documents include, e.g.,group note information, problem list information, hypothesisinformation, and so forth. Video information 606 includes various videosto assist a user in solving a PBL problem and/or a section of PBLproblem. Image information 608 includes various images to assist a userin solving a PBL problem and/or a section of PBL problem. Virtualexamination information 610 includes various virtual examinations toassist a user in solving a PBL problem and/or a section of PBL problem.Generally, a virtual examination is an online, simulated examination ofa physical examination. In an example, server 112 selects one or morevirtual examinations to be included in virtual examination information,based upon the section that the students are working on completing.

In an example, a PBL problem is administrator by a tutor. Referring toFIG. 7, server 112 implements process 700 to promote independentlearning for a PBL problem. In this example, the learning is independentfrom an actual human tutor helping and guiding a student through a PBLproblem. In this example, server 112 implements an electronic tutor(eTutor) module that automatically provides guidance to assist thestudents in learning, e.g., by gradually releasing assets that promoteidentification of various information that is pertinent to a particularsection.

In operation, server 112 receives (702), from a client device used by atutor, a selection of various asset information to assist the studentsin solving a PBL problem. As previously described, the asset informationincludes various solving information, video information, and so forth.Server 112 also receives (704), from the client device used by thetutor, information indicative of a requested level of difficulty, e.g.,an amount of difficulty a student experiences in solving the PBLlearning problem. In this example, server 112 selects (706) one or moreassets (e.g., an item of asset information) to display in a work space(e.g., portion 602 of graphical user interface 600) to promote thesolving of a PBL problem. In this example, various assets are associatedwith various difficulty levels. In this example, server 112 selects, fora particular section, one or more assets for display to the studentsbased on the selected level of difficulty and assets that areappropriate for a section.

In the example of FIG. 7, server 112 enables a user to access one ormore of the identified assets of the appropriate difficulty level. Theassets are shown as research tools 708, e.g., and promote a user'sability to access external resources to research and hence solve a PBLproblem. As shown in FIG. 7, these assets may include word processingdocuments, a web browser, online web searching, instant messaging tools,and so forth. Using the identified assets and solving information (asshown in FIG. 1A), a user generates analysis information, e.g., byselecting a hypothesis, learning objectives, problem list, recommendedaction and so forth. Server 112 performs (710) an electronic tutor(eTutor) analysis operation on the received analysis information. In aneTutor analysis operation, server 112 analyzes a user's analysisinformation, e.g., to determine is the user is correctly identifying ahypothesis, a learning objective, a problem list and/or a recommendedaction for a particular section. In an example, server 112 determinesthat the user has not determined a threshold amount of information,e.g., the user has not correctly identified one or more of thehypothesis, the learning objective, the problem list and/or therecommended action for a particular section. In this example, server 112generates (712) a notification message that notifies the user tore-evaluate the content. In another example, the eTutor analysiscomponent of server 112 generates feedback information (not shown),including, e.g., information to assist a user (e.g., a student) incorrectly identifying issues (e.g., a hypothesis, recommended action,etc.) and aspects of the solving information. In some examples thefeedback information may include information that instructs a user toreview a particular image, a particular video and/or a particularvirtual examination. In other examples, the feedback informationincludes instructions for a student to review a particular medicalarticle or to pay particular attention to a particular aspect of thesolving information. The feedback information may also includeinstructions to consult with a human tutor and/or to consult with aparticular student in the group. In still another example, the feedbackinformation includes hints to promote solving of the PBL problem and/orof the subproblems in the various sections.

In still another example, server 112 determines that the user hasdetermined a threshold amount of information, e.g., the user hascorrectly identified one or more of the hypothesis, the learningobjective, the problem list and/or the recommended action for aparticular section. In this example, server 112 enables (714) the userto view another asset for the particular section, e.g., to enable theuser to correctly identify even more of the hypothesis, the learningobjective, the problem list and/or the recommended action for aparticular section. For example, perhaps the user has correctlyidentified a learning objective, but has not yet correctly identified ahypothesis. In this example, correct identification of a thresholdamount of information includes correct identification of one or more ofthe hypothesis, the learning objective, the problem list and/or therecommended action for a particular section at action 710. Due to theuser's correct identification of the learning objective, the user hasidentified a threshold amount of information, as determined in action710. Based on this determination, server 112 reveals an additional asset(e.g., at action 714) to promote the user's successful identification ofother information, e.g., a recommendation action, a hypothesis, and soforth.

In an example, server 112 repeats actions 706, 710, 712, 714, e.g.,until a user has correctly identified all information (e.g.,recommendation action, hypothesis, and so forth) for a particularsection and/or until the users in a group have reached a consensusaction, causing the group to progress to a new section, in which process700 may be repeated for that new section.

Referring to FIG. 8, server 112 implements process 800 in executing, inparallel, eTutor learning operations 802, 804, 806 for various differentgroups (e.g., groups 1-4). Each of eTutor learning operations 802, 804,806 execute similar operations. For purposes of convenience, and withoutlimitation, the operations included in eTutor learning operation 802 aredescribed. eTutor learning operation 802 includes portion 810, in whichindividual users within a group review assets (for a particularinformation), review solving information and generate—based on thepresented solving information and on the revealed asset—analysisinformation. In this example, a user uses a client device to send toserver 112 an instruction to share the generated analysis informationwith other users in the group. In action 812, server 112 shares withusers' analysis information with other users in the group. In anexample, server 112 may share the analysis information through graphicaluser interface 400 (FIG. 4). As shown in FIG. 8, server 112 may provideusers with various tools 814 through which users may view other usersanalysis information (e.g., in an anonymized format), e.g., a webbrowser for viewing a graphical user interface with anonymized analysisinformation, a word processing document for viewing the anonymizedanalysis information, and so forth. In this example, the users mayengage in a discussion (as shown in action 816) regarding other users'analysis information. Referring back to FIG. 4, users may engage in adiscussion by editing other users' annotations. Referring to FIG. 8, theusers may use one or more of the tools depicted in tools 814, e.g., toengage in a discussion. For example, the users may use an instantmessaging tool to discuss each other's analysis information. Based onthe discussion, the users may modify their analysis information, e.g.,update a recommended action and/or a hypothesis.

In action 818, the eTutor component of server 112 analyzes the modifiedanalysis information, e.g., updates that users have made to originalanalysis information. If the eTutor component determines that athreshold amount of information is correctly determined, the eTutorcomponent releases another asset for the users to view, as previouslydescribed. In this example, if the eTutor component determines that athreshold amount of information is not correctly determined, the eTutorcomponent may execute action 820 in which server 112 notifies a humantutor of a need to assist one or more of the users in the group, e.g.,depending on the severity of the amount of incorrect information. Inthis example, if the number of incorrectly determined items exceeds apredetermined number, then the server 112 determines that the amount ofincorrectly identified information is severe enough to warrant notifyinga real-human tutor. However, in another example, if the number ofincorrectly determined items fails to exceed a predetermined number(i.e., that is indicative of the severity of the amount of difficultythe user is experiencing in correctly identifying information), then theserver 112 may prompt the user to re-evaluate the content, e.g., topromote the user correctly identifying the information.

In this example, server 112 may enable a device used by a human tutor tobecome connected (e.g., via an IM chat, a video conference, and soforth) to a device used by a user who is experiencing problems correctlyidentifying information that is pertinent to the solving of the PBLproblem. In this example, the user consults with the human tutor. Basedon the consultation, the user may update the user's analysisinformation, e.g., by updating a hypothesis, a recommended action, andso forth. At action 822, server 112 determines whether a user mayproceed to a next section and/or proceed to view another asset that isrevealed to the user. Server 112 determines whether the user may proceedby determining whether the user has correctly identified the thresholdamount of information. If the user has correctly identified thethreshold amount of information, the server 112 enables the user toproceed, e.g., by revealing another asset, by enabling the user totransition to another section and so forth.

As shown in FIG. 8, through process 802, server 112 may leverage a realhuman tutor across multiple groups that are working on solving a PBLproblem. In this example, through the eTutor component, server 112 isconfigured to analyze and determine when a real human tutor is requiredto assist students in solving the PBL problem.

Referring to FIG. 9, server 112 implements process 900 in transitioningusers among the various sections in a PBL schema. In operation, server112 generates (902) a PBL problem to be solved by a group of studentsusing the virtual PBL system (e.g., server 112). The PBL may include,for example, medical problem information 150. Server 112 also generates(904) a set of sub-problems that promote solving of the PBL problem.Server 112 generates (906) a medical PBL schema that promotes solving ofthe PBL problem, with the medical PBL schema comprising a plurality ofsections, with one or more of the sections promoting solving of thesub-problems, and with one of the sections for solving of the PBLproblem, with each section associated with (i) a private workenvironment for a particular student to privately analyze the medicalproblem, (ii) a shared, anonymous work environment for the students inthe group to view analysis performed by other students in solving themedical problem, and (iii) solving information to promote solving of aproblem for the section.

In the example of FIG. 9, server 112 transmits (908), to one or moreclient systems used by the students participating in the virtual PBLsystem, the medical PBL schema. In this example, for a particularsection of the medical PBL schema, server 112 receives (910), from aclient device used by the particular student, annotation informationindicative of one or more attributes of the solving information for thesection. In response, server 112 populates (912) private and anonymouswork environments. In particular, server 112 populates the private workenvironment of the particular student with the annotation information.Server 112 also populates the shared, anonymous work environment with ananonymized version of the annotated solving information. In thisexample, server 112 receives (not shown), from client devices used byother of the students, information indicative of edits to the anonymizedversion of the annotated solving information of the particular student.Server 112 also presents (not shown), to the client device used by theparticular student submitting the annotation information, theinformation indicative of the edits. In response to presentation of theedits, server 112 receives, from the client device used by theparticular student information, indicative of a recommended action forthe section. Server 112 also compares the received recommended action toother recommended actions submitted by other students and determines(914) a match among the recommended actions. In response todetermination of the match, server reveals (916) a subsequent section inthe medical PBL schema, e.g., by enabling the medical PBL schema totransition from the current section to a subsequent section in themedical PBL schema.

Embodiments can be implemented in digital electronic circuitry, or incomputer hardware, firmware, software, or in combinations thereof. Anapparatus can be implemented in a computer program product tangiblyembodied or stored in a machine-readable storage device for execution bya programmable processor; and method actions can be performed by aprogrammable processor executing a program of instructions to performfunctions by operating on input data and generating output. Theembodiments described herein, and other embodiments of the invention,can be implemented advantageously in one or more computer programs thatare executable on a programmable system including at least oneprogrammable processor coupled to receive data and instructions from,and to transmit data and instructions to, a data storage system, atleast one input device, and at least one output device. Each computerprogram can be implemented in a high-level procedural or object orientedprogramming language, or in assembly or machine language if desired; andin any case, the language can be a compiled or interpreted language.

Processors suitable for the execution of a computer program include, byway of example, both general and special purpose microprocessors, andany one or more processors of any kind of digital computer. Generally, aprocessor will receive instructions and data from a read-only memory ora random-access memory or both. The essential elements of a computer area processor for executing instructions and one or more memory devicesfor storing instructions and data. Generally, a computer will alsoinclude, or be operatively coupled to receive data from or transfer datato, or both, one or more mass storage devices for storing data, e.g.,magnetic, magneto optical disks, or optical disks. Computer readablemedia for embodying computer program instructions and data include allforms of non-volatile memory, including by way of example semiconductormemory devices, e.g., EPROM, EEPROM, and flash memory devices; magneticdisks, e.g., internal hard disks or removable disks; magneto opticaldisks; and CD ROM and DVD-ROM disks. The processor and the memory can besupplemented by, or incorporated in special purpose logic circuitry. Anyof the foregoing can be supplemented by, or incorporated in, ASICs(application-specific integrated circuits).

To provide for interaction with a user, embodiments can be implementedon a computer having a display device, e.g., a LCD (liquid crystaldisplay) monitor, for displaying data to the user and a keyboard and apointing device, e.g., a mouse or a trackball, by which the user canprovide input to the computer. Other kinds of devices can be used toprovide for interaction with a user as well; for example, feedbackprovided to the user can be any form of sensory feedback, e.g., visualfeedback, auditory feedback, or tactile feedback; and input from theuser can be received in any form, including acoustic, speech, or tactileinput.

Embodiments can be implemented in a computing system that includes aback end component, e.g., as a data server, or that includes amiddleware component, e.g., an application server, or that includes afront end component, e.g., a client computer having a graphical userinterface or a Web browser through which a user can interact with animplementation of embodiments, or any combination of such back end,middleware, or front end components. The components of the system can beinterconnected by any form or medium of digital data communication,e.g., a communication network. Examples of communication networksinclude a local area network (LAN) and a wide area network (WAN), e.g.,the Internet.

The system and method or parts thereof may use the “World Wide Web” (Webor WWW), which is that collection of servers on the Internet thatutilize the Hypertext Transfer Protocol (HTTP). HTTP is a knownapplication protocol that provides users access to resources, which maybe data in different formats such as text, graphics, images, sound,video, Hypertext Markup Language (HTML), as well as programs. Uponspecification of a link by the user, the client computer makes a TCP/IPrequest to a Web server and receives data, which may be another Web pagethat is formatted according to HTML. Users can also access other pageson the same or other servers by following instructions on the screen,entering certain data, or clicking on selected icons. It should also benoted that any type of selection device known to those skilled in theart, such as check boxes, drop-down boxes, and the like, may be used forembodiments using web pages to allow a user to select options for agiven component. Servers run on a variety of platforms, including UNIXmachines, although other platforms, such as Windows 2000/2003, WindowsNT, Sun, Linux, and Macintosh may also be used. Computer users can viewdata available on servers or networks on the Web through the use ofbrowsing software, such as Firefox, Netscape Navigator, MicrosoftInternet Explorer, or Mosaic browsers. The computing system can includeclients and servers. A client and server are generally remote from eachother and typically interact through a communication network. Therelationship of client and server arises by virtue of computer programsrunning on the respective computers and having a client-serverrelationship to each other.

Other embodiments are within the scope and spirit of the descriptionclaims. Additionally, due to the nature of software, functions describedabove can be implemented using software, hardware, firmware, hardwiring,or combinations of any of these. Features implementing functions mayalso be physically located at various positions, including beingdistributed such that portions of functions are implemented at differentphysical locations.

The use of the term “a” herein and throughout the application is notused in a limiting manner and therefore is not meant to exclude amultiple meaning or a “one or more” meaning for the term “a.”Additionally, to the extent priority is claimed to a provisional patentapplication, it should be understood that the provisional patentapplication is not limiting but includes examples of how the techniquesdescribed herein may be implemented.

A number of exemplary embodiments of the invention have been described.Nevertheless, it will be understood by one of ordinary skill in the artthat various modifications may be made without departing from the spiritand scope of the invention.

What is claimed is:
 1. A computer-implemented method, comprising:selecting, by a virtual problem-based learning (PBL) system, informationindicative of a medical profile of a patient; accessing, by the virtualPBL system, information indicative of a team of students using thevirtual PBL system; generating, by the virtual PBL system and based onthe medical profile, an medical PBL schema comprising a medical problemto be solved by the team of students; generating a plurality of sectionsin the medical PBL schema, with each section promoting solving of themedical problem, and with each section associated with (i) a privatework environment for a student to privately analyze the medical problem,and (ii) a shared, anonymous work environment for the students to viewanalysis performed by other students in solving the medical problem; andtransmitting, to one or more client systems used by the studentsparticipating in the virtual PBL system, the medical PBL schema.
 2. Thecomputer-implemented method of claim 1, further comprising: receiving,from the one or more client systems, analysis information indicative ofan analysis performed by the one or more students; evaluating thereceived analysis information; generating, based on evaluating, feedbackinformation; and transmitting the feedback information to at least oneof the one or more client systems.
 3. The computer-implemented method ofclaim 1, further comprising: associating one or more research tools withthe private work environment, wherein the one or more research tools areselected from a group consisting of an Internet browser and an instantmessaging tool.
 4. The computer-implemented method of claim 1, furthercomprising: transmitting, to at least one of the one or more clientdevices, outcome data indicative of outcomes of patients with medicalprofiles that are similar to the selected medical profile, with theoutcome data comprising comorbidity data.
 5. The method of claim 1,further comprising: receiving, from the one or more client systems,analysis information indicative of an analysis performed by the one ormore students; for a particular student, populating the private workenvironment of the student with a portion of the analysis informationthat is associated with the particular student; generating an anonymizedview of the private work environment of the student; populating theshared, anonymous work environment with the anonymized view of theprivate work environment of the particular student and with anonymizedviews of other private work environments of others of the students. 6.The computer-implemented method of claim 5, further comprising:receiving, from at least one of the one or more client systems used by afirst student, information indicative of an annotation of informationdisplayed in one of the anonymized views of a second student, with thefirst student differing from the second student; and updating the one ofthe anonymized views with the received annotation to promote learning bythe second student.
 7. The computer-implemented method of claim 1,further comprising: for a particular first section: receiving, from theone or more client systems, first analysis information indicative of ananalysis performed by the one or more students; determining, from thereceived first analysis information, first recommended actions that arerecommended by each of the students; determining an inconsistency amongthe first recommended actions; providing, to the one or more clientsystems, evaluation information to promote an understanding by thestudents of the medical problem; receiving, from the one or more clientsystems, second analysis information indicative of another analysisperformed by the one or more students; determining, from the receivedsecond analysis information, second recommended actions that arerecommended by each of the students; determining consistency among thesecond recommended actions; causing, based on determination of theconsistency, the medical PBL schema to progress from the first sectionto the second section.
 8. The computer-implemented method of claim 1,further comprising: retrieving information indicative of a correctaction for the particular first section; responsive to determining theconsistency among the second recommended actions, generating anotification of whether the second recommended actions corresponds tothe correct action.
 9. The computer-implemented method of claim 8,wherein the second recommended actions comprise an action to performsurgery.
 10. The computer-implemented method of claim 1, furthercomprising: generating highlighting tools for annotation of the medicalprofile, wherein each one of the highlighting tools corresponds toattributes of the medical problem; receiving, by the computer system,information indicative of annotations of the medical profile;determining, by the computer system, at least a portion of theannotations that is selected using a particular one of the highlightingtools; identifying which one of the attributes corresponds to theparticular one of the highlighting tools; and storing, in a datarepository, the determined portion of the annotations in associationwith the identified one of the attributes.
 11. A system comprising: oneor more processing devices; and one or more computer-readable mediastoring instructions that are executable by the one or more processingdevices to perform operations comprising: selecting informationindicative of a medical profile of a patient; accessing informationindicative of a team of students using the virtual PBL system;generating, based on the medical profile, an medical PBL schemacomprising a medical problem to be solved by the team of students;generating a plurality of sections in the medical PBL schema, with eachsection promoting solving of the medical problem, and with each sectionassociated with (i) a private work environment for a student toprivately analyze the medical problem, and (ii) a shared, anonymous workenvironment for the students to view analysis performed by otherstudents in solving the medical problem; and transmitting, to one ormore client systems used by the students participating in the virtualproblem-based learning system, the medical PBL schema.
 12. The system ofclaim 11, wherein the operations further comprise: receiving, from theone or more client systems, analysis information indicative of ananalysis performed by the one or more students; evaluating the receivedanalysis information; generating, based on evaluating, feedbackinformation; and transmitting the feedback information to at least oneof the one or more client systems.
 13. The system of claim 11, whereinthe operations further comprise: receiving, from the one or more clientsystems, analysis information indicative of an analysis performed by theone or more students; for a particular student, populating the privatework environment of the student with a portion of the analysisinformation that is associated with the particular student; generatingan anonymized view of the private work environment of the student;populating the shared, anonymous work environment with the anonymizedview of the private work environment of the particular student and withanonymized views of other private work environments of others of thestudents.
 14. The system of claim 11, wherein the operations furthercomprise: for a particular first section: receiving, from the one ormore client systems, first analysis information indicative of ananalysis performed by the one or more students; determining, from thereceived first analysis information, first recommended actions that arerecommended by each of the students; determining an inconsistency amongthe first recommended actions; providing, to the one or more clientsystems, evaluation information to promote an understanding by thestudents of the medical problem; receiving, from the one or more clientsystems, second analysis information indicative of another analysisperformed by the one or more students; determining, from the receivedsecond analysis information, second recommended actions that arerecommended by each of the students; determining consistency among thesecond recommended actions; causing, based on determination of theconsistency, the medical PBL schema to progress from the first sectionto the second section.
 15. The system of claim 14, wherein theoperations further comprise: retrieving information indicative of acorrect action for the particular first section; and responsive todetermining the consistency among the second recommended actions,generating a notification of whether the second recommended actionscorresponds to the correct action.
 16. One or more computer-readablemedia storing instructions that are executable by one or more processingdevices to perform operations comprising: selecting informationindicative of a medical profile of a patient; accessing informationindicative of a team of students using the virtual PBL system;generating, based on the medical profile, an medical PBL schemacomprising a medical problem to be solved by the team of students;generating a plurality of sections in the medical PBL schema, with eachsection promoting solving of the medical problem, and with each sectionassociated with (i) a private work environment for a student toprivately analyze the medical problem, and (ii) a shared, anonymous workenvironment for the students to view analysis performed by otherstudents in solving the medical problem; and transmitting, to one ormore client systems used by the students participating in the virtualproblem-based learning system, the medical PBL schema.
 17. The one ormore computer-readable media of claim 16, wherein the operations furthercomprise: receiving, from the one or more client systems, analysisinformation indicative of an analysis performed by the one or morestudents; evaluating the received analysis information; generating,based on evaluating, feedback information; and transmitting the feedbackinformation to at least one of the one or more client systems.
 18. Theone or more computer-readable media of claim 16, wherein the operationsfurther comprise: receiving, from the one or more client systems,analysis information indicative of an analysis performed by the one ormore students; for a particular student, populating the private workenvironment of the student with a portion of the analysis informationthat is associated with the particular student; generating an anonymizedview of the private work environment of the student; populating theshared, anonymous work environment with the anonymized view of theprivate work environment of the particular student and with anonymizedviews of other private work environments of others of the students. 19.The one or more computer-readable media of claim 16, wherein theoperations further comprise: for a particular first section: receiving,from the one or more client systems, first analysis informationindicative of an analysis performed by the one or more students;determining, from the received first analysis information, firstrecommended actions that are recommended by each of the students;determining an inconsistency among the first recommended actions;providing, to the one or more client systems, evaluation information topromote an understanding by the students of the medical problem;receiving, from the one or more client systems, second analysisinformation indicative of another analysis performed by the one or morestudents; determining, from the received second analysis information,second recommended actions that are recommended by each of the students;determining consistency among the second recommended actions; causing,based on determination of the consistency, the medical PBL schema toprogress from the first section to the second section.
 20. A methodcomprising: generating, by a virtual problem-based learning (PBL)system, a PBL problem to be solved by a group of students using thevirtual PBL system; generating a set of sub-problems that promotesolving of the PBL problem; generating, by the virtual PBL system, amedical PBL schema that promotes solving of the PBL problem, with themedical PBL schema comprising a plurality of sections, with one or moreof the sections promoting solving of the sub-problems, and with one ofthe sections for solving of the PBL problem, with each sectionassociated with (i) a private work environment for a particular studentto privately analyze the medical problem, (ii) a shared, anonymous workenvironment for the students in the group to view analysis performed byother students in solving the medical problem, and (iii) solvinginformation to promote solving of a problem for the section;transmitting, to one or more client systems used by the studentsparticipating in the virtual PBL system, the medical PBL schema; for asection, receiving, from a client device used by the particular student,annotation information indicative of one or more attributes of thesolving information for the section; populating the private workenvironment of the particular student with the annotation information;populating the shared, anonymous work environment with an anonymizedversion of the annotated solving information; receiving, from clientdevices used by other of the students, information indicative of editsto the anonymized version of the annotated solving information of theparticular student; presenting, to the client device used by theparticular student submitting the annotation information, theinformation indicative of the edits; in response to presentation of theedits, receiving, from the client device used by the particular studentinformation, indicative of a recommended action for the section;comparing the received recommended action to other recommended actionssubmitted by other students; determining a match among the recommendedactions, in response to determination of the match, enabling the medicalPBL schema to transition from the current section to a subsequentsection in the medical PBL schema.